Is Increased Water Consumption Among Older Adults Associated with Improvements in

Glycemia?

Adrienne Ginter Clark

Thesis submitted to the faculty of the Virginia Polytechnic Institute and State University in

partial fulfillment of the requirements for the degree of

Master of Science

In

Human Nutrition, Foods and Exercise

Brenda M. Davy, Chair

Kevin P. Davy

Jyoti S. Savla

May 1, 2013

Blacksburg, VA

Keywords: older adults, diabetes, glucose, water consumption, hydration

Is Increased Water Consumption Among Older Adults Associated with Improvements in

Glycemia?

Adrienne Ginter Clark

ABSTRACT

The high rates of obesity and impaired glycemia in older adults place these individuals at

risk for developing diabetes. Dehydration, glucose tolerance, and insulin resistance are related.

Many older adults do not achieve the Dietary Reference Intake (DRI) for water, and aging and

dehydration are both associated with decreased glucose tolerance. Conversely, weight loss is

associated with improvements in glucose tolerance. For older adults following a hypocaloric diet,

additional water consumption may lead to greater weight loss. Furthermore, research suggests an

association between insulin resistance and arginine vasopressin (AVP), the hormone responsible

for regulating body water retention. Analysis of the association between plasma copeptin (an

AVP derivative) and fasting glucose, insulin, and homeostasis model assessment of insulin

resistance (HOMA-IR) may provide further insight into the relationship between dehydration

and diabetes risk.

To our knowledge, few investigations have addressed this relationship between

dehydration, impaired glycemia, and insulin resistance and how increasing water consumption

may influence diabetes risk. Our purpose was to investigate the possibility that increased water

consumption among older adults (n=29, BMI=31+1 kg/m2, age=62+1 years) could improve

glycemia beyond that observed with weight loss, as well as associations between plasma

copeptin and diabetes risk. Analysis of diabetes-related variables for subjects grouped according

to study intervention group, amount of drinking water consumed, or pair-matched for weight loss

and gender did not reveal significant differences between groups. Improvements in fasting

insulin for water group participants, as well as correlations between hydration and insulin

resistance support the need for future investigations.

iii

TABLE OF CONTENTS

Abstract ii

Table of Contents iii

List of Figures iv

List of Tables iv

CHAPTER 1: Introduction 1

Water Intake in Older Adults 1

Associations Between Copeptin, Hydration, and Diabetes Risk 2

Effects of Inadequate Water Consumption 3

CHAPTER 2: Is Increased Water Consumption Among Older Adults Associated with

Improvements in Glycemia?

5

Introduction 5

Review of Literature 5

The Effects of Weight Loss and Water Consumption on Glucose Control in

Older Adults

5

Water Consumption May Enhance Weight Loss 7

Materials and Methods 9

Statistical Analysis 10

Results 11

Discussion 12

Figures and Tables 15

CHAPTER 3: Conclusions and Implications for Future Research 19

References 20

iv

LIST OF FIGURES

Chapter 2:

Figure 1: Associations between aging, water consumption, and diabetes risk; and areas to

target for intervention. (Page 15)

LIST OF TABLES

Chapter 2:

Table 1: Results: Summary table of participant characteristics and variables associated

with weight loss, water consumption, and diabetes risk (n=29). (Page 16)

Table 2: Results: Group differences according to two drinking water categories at week

12 of the intervention (n=25). (Page 17)

Table 3: Results: Ranges and means for variables related to diabetes risk among

participants pair-matched for gender and kilograms of weight lost (n=12). (Page 18)

1

CHAPTER 1: Introduction

Water Intake in Older Adults

Water is a vital nutrient necessary for life. Water plays many significant roles within the

human body and because humans cannot obtain adequate water via metabolism or food ingestion

alone, beverage consumption is critical for maintaining hydration status (1). Oftentimes

recommendations on daily water consumption are forgotten (1), thus many individuals may not

understand the importance of drinking enough water. For the elderly population, adequate fluid

intake and hydration status become especially important. Decreased renal function with aging

leads to impairments in renal-concentrating and sodium-conserving ability, conditions that are

associated with volume depletion and hypernatremia in the elderly (2). In healthy individuals,

depleted volume and elevated sodium levels will prompt thirst and subsequent fluid intake to

restore hydration status. It is important to note that fluid intake is the only method in which to

replenish water deficits, so the thirst sensation is imperative for fluid and electrolyte homeostasis

(3). However, thirst is often blunted in elderly subjects and inadequate fluid intake may increase

risk of dehydration and hypernatremia (2).

Hypodipsia (abnormally diminished thirst) in the elderly population is well established. A

study that examined the effects of dehydration on thirst and urine and plasma markers in the

elderly as compared to younger adults found that after fluid deprivation, the elderly subjects

experienced significant increases in plasma sodium concentration (140.2+0.4 to 143.2+0.5

mmol/L) and osmolality (288.4+1.3 to 296.0+1.2 mOsm/kg of water) while the younger group

had nonsignificant increases of both variables (3). The younger participants experienced a strong

thirst response that prompted them to drink enough fluids to replenish their body fluids while the

elderly did not (3). These results clearly indicated a deficit in thirst and subsequent water intake

in the older adults following dehydration (3). A wealth of literature exists that further

demonstrates hypodipsia in the elderly despite elevated plasma sodium levels and osmolality.

However, the physiological mechanisms behind blunted thirst in the elderly remain unclear.

Under normal conditions, the feedback mechanisms of osmotic control pathways and

baroreceptor pathways will maintain water balance and bring disturbed plasma osmolarity back

to normal. The osmoreceptors located within the hypothalamus are responsible for stimulating

thirst and sodium appetite, causing an individual to drink when plasma osmolarity increases.

2

Additionally, peripheral osmoreceptors in the oropharyngeal area are stimulated by the dryness

of the oral and esophageal mucosa that occurs in a dehydrated state. These osmoreceptors are

responsible for stimulating secretion of arginine vasopressin (AVP), which causes an antidiuretic

effect in the kidneys and retention of water under conditions of negative water balance and

elevated plasma osmolarity (4). A less sensitive system responds to decreases in plasma volume

or arterial pressure that occur with negative water balance. Baroreceptors within blood vessels

and the heart are stimulated when hypervolemia occurs, causing suppression of AVP secretion.

Conversely, AVP secretion increases in hypovolemia, leading to water retention (4).

Dysfunctions within these systems are among the proposed mechanisms for decreased thirst in

the elderly. Impairments in osmoreceptors that respond to elevated plasma osmolarity and

baroreceptors that respond to decreased plasma volume may occur in older adults (3). Alterations

in oropharyngeal factors (like dry mouth and taste), central nervous system dysfunction, and

alterations in neuroendocrine function that accompany age (specifically the activity of the renin-

angiotensin-aldosterone system and levels of atrial natriuretic peptide) may also contribute to

hypodipsia and dehydration in the elderly (3). However, additional research is needed to clearly

demonstrate causes for blunted thirst in the elderly.

Associations Between Copeptin, Hydration, and Diabetes Risk

Arginine vasopressin is a principal regulator of body water balance. It acts upon the renal

collecting ducts by increasing water permeability of the apical membrane and promoting free

water reabsorption (5). AVP is synthesized as prepro-hormone with four constituent parts: a

signal peptide, the AVP hormone, a carrier protein, and the glycoprotein copeptin (5). Plasma

AVP is unstable, is largely bound to platelets, and is rapidly cleared from the bloodstream. These

factors combined with a lack of reliable AVP assays have limited the use of circulating AVP

levels in clinical diagnostics (6). Alternatively, copeptin is stable ex vivo in plasma and sensitive

sandwich immunoassays are available for detecting copeptin in human plasma or serum.

Researchers believe that copeptin should represent the release of AVP (similar to the situation of

C-peptide and insulin) (5), and correlations found between copeptin and AVP indicate that

copeptin analysis is an acceptable alternative to AVP assays (6). Furthermore, recent research

suggests that the AVP system plays a role in glucose homeostasis, insulin resistance, and

diabetes mellitus (7). A large population-based prospective study found higher copeptin

3

concentrations among individuals with diabetes compared to those without diabetes, positive

associations between copeptin, fasting blood glucose, and plasma insulin in those without

diabetes, and significantly higher copeptin concentrations at baseline for those normoglycemic

subjects who subsequently developed new-onset diabetes (7). Additionally, a cross-sectional

study reports a positive correlation of plasma copeptin with components of metabolic syndrome

(BMI, waist circumference, fasting serum glucose and insulin levels, HOMA-IR, presence of

diabetes, and serum triglycerides) when adjusted for age and sex (8). These findings imply that

copeptin is associated with the presence of metabolic syndrome and may be a predictor for

diabetes development (independent of renal function, and diabetes risk factors such as fasting

blood glucose and insulin). Proposed underlying mechanisms for the role of the AVP system in

the pathophysiology of diabetes include action upon AVP receptors and stress-induced elevation

of AVP levels (7, 8). An additional relationship may exist between copeptin, aging, and renal

function. Older subjects experienced the most pronounced association between low copeptin

levels, lower urine volume and higher urine osmolarity (9). Elevated copeptin in the elderly may

indicate decline in renal function and/or reduced sensitivity to AVP, and researchers suggest that

this population is likely to profit from interventions geared toward increasing water intake (9).

Effects of Inadequate Water Consumption

The current Adequate Intake (AI) for total water (from drinking water, beverages, and

food) for adults over 50 years is 3.7 L/day and 2.7 L/day for males and females, respectively

(10). Of this total water intake, it is normally assumed that 70-80% comes from beverages, and

20-30% comes from food (1). Thus, total daily beverage intake (including drinking water) should

amount to 3.0 L/day for males and 2.2 L/day for females over 50 years of age (2). Data obtained

from national health surveys on patterns of daily beverage consumption in the United States

show that older adults are not meeting these recommendations. Trends for total beverage intake

by age indicate a sharp decrease for adults over 60 years of age (11). Researchers suggest that the

very low intake of only 2.1 L/day in this age bracket may be a potential health concern (11).

Rates of plain water consumption also decrease with age. Data obtained from the National

Health and Nutrition Examination Survey (NHANES) 2005-2008 show that adults aged 40-59

years drink about 1.1 L of plain water per day. Persons over 60 drink even less plain water,

4

averaging only 0.73 L/day and 0.83 L/day for males and females, respectively (12). These data

show that the older adult population is clearly not drinking enough water.

Inadequate water consumption can lead to disruptions in hydration status, placing older

individuals at risk for numerous health complications. Dehydration may result in impaired

cognitive function and motor control, increased resting heart rate, increased risk of infection (i.e.

urinary tract infections), kidney and gall stone formation, higher incidence of colon and bladder

cancer, heart arrhythmias, blood clots, and mitral valve prolapse (2). Furthermore, both women

and men who experienced mild dehydration (a loss of only 1.39% and 1.59% of body mass,

respectively) demonstrated cognitive impairment and mood changes (13, 14). Regrettably,

research has found that as many as 40% of older adults are dehydrated as evidenced by having

hypertonic plasma (15). This hypertonicity is also associated with aging, decreased glucose

tolerance, diabetes, and obesity (15, 16). For individuals who have diabetes, dehydration worsens

diabetes control (2). Furthermore, adults with normal baseline fasting glucose who participated

in a 9-year follow up study experienced an inverse association between water intake and the

development of hyperglycemia (17). Odds ratios were calculated to determine the relationship

between volume of self-reported daily water consumption (categorized as <0.5 L, 0.5 to <1.0 L,

and >1.0 L) and onset of hyperglycemia. The results (odds ratios of 1.00, 0.64, and 0.73

respectively) indicated that subjects who consumed the least water had the highest occurrence of

hyperglycemia (17). While future studies are warranted to determine whether increased water

intake may be protective against development of hyperglycemia, these results demonstrate

positive benefits of water consumption on blood glucose regulation.

The combination of blunted thirst, inadequate fluid intake, and impaired glucose

homeostasis in older adults places these individuals at risk for numerous health complications.

Thus, increasing water consumption to maintain hydration is critical for preventing illness

induced by fluid deficits, as well as preventing impairments in blood glucose control.

5

CHAPTER 2: Is Increased Water Consumption Among Older Adults Associated with

Improvements in Glycemia?

I. Introduction

It is known that increasing water consumption (17, 18), or reducing body weight (19-22),

will lead to improvements in glucose tolerance in older adults. Additional research has shown

that drinking more water may optimize weight loss in this population (23-26), as well. If it is

found that older adults who lose weight while increasing water consumption experience greater

improvements in glycemia than that observed with weight loss alone, this may be a method for

reducing diabetes risk factors in this population (Figure 1). Additionally, the negative

consequences of dehydration including impaired cognitive function and motor control, increased

resting heart rate, infections, and kidney and gall stone formation (2) may be avoided in older

adults through increased water consumption.

If weight loss coupled with improved hydration status leads to improvements in fasting

glucose concentration and insulin resistance in older adults, this dietary strategy could be

recommended by dietitians counseling individuals at risk for diabetes. Current clinical practice

guidelines do not place emphasis on increasing water consumption in older adults; therefore, the

results of this investigation may have important clinical implications for health care providers.

Elucidating a simple method for improving glycemia in this population could positively benefit

the elderly patient by potentially limiting chronic illnesses resulting in a healthier and more

rewarding life free from diabetes complications. Additionally, if clinicians are required to

emphasize the importance of water consumption (as well as a healthy lifestyle) for all age

groups, this preventative approach may lessen the high rates of diabetes seen later in life.

Therefore, the purpose of this study is to determine if glycemia is improved with increased water

consumption beyond that observed with weight loss among older adults.

II. Review of Literature

The Effects of Weight Loss and Water Consumption on Glucose Control in Older Adults

It is well established that decreased glucose tolerance and insulin resistance are often

present in obese individuals and may develop with aging (19). The changes in body composition,

namely increased body weight, fat mass, and fat distribution (abdominal and visceral adiposity)

that occur with aging are associated with hyperinsulinemia (which is tethered to insulin

resistance) and elevated plasma glucose (19, 27). Impaired fasting glucose (IFG) and impaired

6

glucose tolerance (IGT) are states of abnormal glucose regulation that fall between the

conditions of normal glucose homeostasis and diabetes (28). An elevated fasting plasma glucose

(FPG) reading between 100-126 mg/dl indicates IFG, and a reading between 140-200 mg/dl

following a 75 g glucose load on the oral glucose tolerance test (OGTT) indicates IGT (28). Both

IFG and IGT are indicators of abnormal glucose regulation; individuals with impaired glycemia

in addition to hyperinsulinemia and/or insulin resistance often develop diabetes and other

associated metabolic disorders (27, 28).

Individuals with obesity, impaired glucose tolerance, or type 2 diabetes mellitus

experience increases in insulin sensitivity and improvements in glucose tolerance with weight

loss (19). Two long-term randomized clinical trials (the Diabetes Prevention Program and Look

AHEAD) present strong evidence for the positive impact of lifestyle interventions aimed at

weight loss on development of diabetes (29). Participants enrolled in the Diabetes Prevention

Program (DPP) (n=3234) were overweight adults (mean BMI=34.0 kg/m2, mean age=51 years)

at an elevated risk for the development of type 2 diabetes (FPG: 95-125 mg/dl; IGT after OGTT:

140-199 mg/dl) (22). Goals for participants assigned to the intensive lifestyle intervention group

included a 7% loss and maintenance of body weight via healthy diet and 150 min/week of

moderate intensity physical activity. The incidence of diabetes was 58% lower in the intensive

lifestyle intervention group than in the placebo group, and FPG concentration was significantly

lower for participants in the lifestyle-intervention group at the end of the follow-up period (22).

The results of this large trial show that lifestyle modification (resulting in weight loss) is a highly

effective means for delaying or preventing type 2 diabetes in the susceptible older adult

population.

In addition, middle-aged and older obese men who lost an average of 19% of their body

fat mass experienced a decrease in the prevalence of IGT from 57% of subjects to 40%. Fasting

insulin levels decreased by 20% (90 to 72 pmol/L) with weight loss in these individuals (20).

Other studies show that the incidence of diabetes can be reduced through lifestyle interventions,

namely improved diet and increased physical activity that lead to reductions in body weight (21).

Middle-aged overweight subjects (n=522, mean age=55 years, mean BMI=31 kg/m2) with

impaired glucose homeostasis who received personalized dietary and physical activity

counseling lost significantly more weight than the control group (3.5+5 vs. 0.8+4.4 kg) and

7

experienced significant improvements in glucose tolerance (FPG: -0.1 +0.7 vs. +0.2+0.8

mmol/L, P<0.001; 2 hours after OGTT: -0.8+2.1 vs. +0+2.5 mmol/L, P<0.001) at the end of the

2-year intervention (21). Participants in the intervention group also experienced significantly

greater reductions in serum insulin concentration following the 2-hr OGTT (21).

We have previously mentioned the inverse association found among water consumption

and development of hyperglycemia (17). Most solutes found within plasma are dissociated

sodium salts, but ions (like potassium and calcium), urea, and glucose also contribute to plasma

osmolality. In conditions of dehydration, total body water decreases below normal levels without

a reduction in solutes, which most notably leads to hypernatremia, but may also raise plasma

glucose (30). Therefore, decreased glucose tolerance may be related to increased solute

concentration resulting from dehydration, and increasing water consumption may have

preventative effects on elevations in plasma glucose. Furthermore, selecting water over caloric

beverages may be a tool for improving both hydration and glycemia. Non-diabetic overweight

and obese adults who participated in the 6 month CHOICE weight loss trial used noncaloric

beverage substitution alone as a primary weight loss strategy (18). Compared to the attention

control (AC) group, participants who replaced caloric beverages with water (WA) significantly

improved fasting glucose (WA: -3.21 vs. AC: 0.59 mg/dl) and hydration (urine osmolality WA:

-93.83 vs. AC: 32.76 mOsmol/kg) despite similar or smaller weight loss in the water group

(mean % weight loss: 2.03% vs. 1.76%) (18). The results of this weight loss intervention indicate

that drinking more water (as opposed to calorie-containing beverages) may contribute to

improved hydration and fasting glucose in the overweight older adult population, even without

modest weight loss. Although fasting glucose was a parameter measured in this study, blood

glucose regulation was not specifically targeted by the beverage replacement weight loss

intervention. Most current research concerning improved glucose tolerance focuses on the

positive effects of weight loss, and not water consumption exclusively, on blood glucose control.

Water Consumption May Enhance Weight Loss

We have explained that 1) proper hydration is important for many health outcomes

including blood glucose regulation and 2) body weight loss can improve glucose tolerance.

Recent studies have demonstrated an additional benefit of increased water consumption: the

ability to enhance weight loss in older adults.

8

A secondary analysis of the Stanford A to Z clinical weight loss trial (in which

overweight pre-menopausal women were assigned to four popular weight loss diets) focused on

those subjects who consumed less than 1 liter of drinking water per day at baseline. This subset

of individuals (n=173) had significantly greater weight loss once water intake increased to >1

L/day compared to those with continual intake of <1 L/day (24). Potential mechanisms for the

ability of water to promote weight loss include an increase in energy expenditure and/or rates of

lipolysis, due to the thermogenic effect from warming the water to body temperature (24, 26).

Researchers have found that drinking 500 ml of water increases metabolic rate by 30% in

healthy, normal weight adults (mean age=28 years) when the ingested water is warmed from 22

to 37oC (26). Furthermore, an increase in lipid metabolism was found among the male

participants (respiratory quotient changed from 0.841 to 0.79) (26). It is estimated that increasing

water consumption by 1.5 L/day would result in an additional energy expenditure of about 48

kcal (26), allowing for augmented weight loss for those drinking more water.

Additional studies have targeted increased water consumption as an effective weight-

control strategy in overweight and obese older adults due to a reduction in meal energy intake.

Individuals (n=24, mean BMI=34.3+1.2 kg/m2, age=55-75 years) who consumed a 500 ml water

preload prior to meal consumption had a significantly lower meal energy intake (EI) compared

with a control condition in which no pre-meal water was consumed (74+23 kcal difference

between the two conditions) (23). This approximate 13% reduction in EI following a water

preload may be due to delayed gastric emptying resulting in sensations of fullness and reduced

hunger in the older adult population (23).

A follow-up investigation of the aforementioned water preload study sought to determine

if premeal water consumption would facilitate weight loss in overweight/obese older adults

(BMI=25-40 kg/m2, age=55-75 years), and if a resulting reduced meal EI was sustained after 12

weeks (25). At the end of the 12-week weight-loss intervention, participants assigned to the

water preload condition (hypocaloric diet + 500 ml H2O before each of 3 daily meals) showed a

44% greater rate of weight loss than did those in the non-water group (hypocaloric diet only)

(25). This approximate 2 kg greater weight loss in the water group may be attributed to delayed

gastric emptying seen with advancing age and increased sensations of fullness that lead to

9

reduced meal EI. However, the exact mechanisms by which the reduced energy intake occurs, as

well as the long-term effects of this intervention strategy, are still being investigated.

These findings suggest that including increased water consumption as part of a weight

loss regimen for overweight older adults may lead to greater reductions in body weight, thus

resulting in even better improvements in glycemia and insulin sensitivity than with weight loss

alone (Figure 1). Augmenting weight loss with increased water consumption may have the

potential to reduce the incidence of and progression to type 2 diabetes for overweight adults with

diminished glucose control. To our knowledge, there are no studies to date that have directly

addressed the possibility that increasing water intake in combination with weight loss in the

overweight older adult population will lead to considerable improvements in fasting glucose and

reductions in diabetes risk factors, or the exact mechanisms behind this additive effect. Available

research has suggested beneficial effects on glucose tolerance, but has not directly targeted

diabetes risk factors, such as IFG, IGT, and insulin resistance.

III. Materials and Methods

This retrospective analysis utilized data collected at Virginia Tech (25). The purpose of

the original study was to determine if premeal water consumption of 500 ml would facilitate

weight loss in a population of obese and overweight older adults over 12 weeks. Additionally,

the study sought to determine if the reduction of meal energy intake observed with premeal water

consumption would be sustained after a 12-week period. Participants who were eligible for the

study were overweight or obese (BMI=25-40 kg/m2), between the ages of 55-75 years, weight

stable (+2 kg, >1 year), and non-smokers. Assessments included height, measured in meters

without shoes using a wall mounted stadiometer; weight, measured in light clothing and no shoes

to the nearest 0.1 kg on a digital scale (Scale-Tronix model 5002, Wheaton, IL); urine, collected

over 24 hours for assessment of total volume, and specific gravity using a refractometer (Fisher

UriSystem; Fisher Scientific, Hampton, NH). Although not reported in the original published

article, venous blood drawn in a fasted state was used to determine fasting plasma glucose and

insulin concentration. Plasma glucose concentration was measured using a YSI glucose analyzer

(model 2300, Yellow Springs Instruments) and plasma insulin concentration was quantified

using a commercially available ELISA (Linco Research, Inc.). Insulin resistance (previously

unreported) was estimated using homeostasis model assessment (HOMA) and an insulin

10

resistance score (HOMA-IR) was computed with the following formula: fasting plasma glucose

(mmol/L) times fasting serum insulin (mU/L) divided by 22.5 (31). High HOMA-IR values

indicate low insulin sensitivity (insulin resistance), and low HOMA-IR values indicate high

sensitivity to insulin (31). Following completion of baseline assessments, participants were

randomly assigned to one of two diet groups for 12 weeks: (i) hypocaloric diet + 500 ml water

prior to each daily meal (water group), or (ii) hypocaloric diet alone (non-water group).

Participants’ body weight was measured weekly in the laboratory, and daily premeal water

consumption logs were submitted by the water group at this time to monitor compliance. For the

present investigation, plasma copeptin was assessed at baseline and at week 12 of the weight loss

intervention, using an enzyme immunoassay (EIA) kit from Phoenix Pharmaceuticals (Cat #EK-

065-32).

Statistical Analysis

Statistical analyses were performed using SPSS statistical analysis software (versions

12.0 and 20.0 for Windows, 2003, 2011 SPSS, Inc., Chicago, IL). Independent sample t-tests

were used to assess group differences at baseline, as well as differences in intervention outcomes

including BMI, body weight, drinking water consumed, urinary specific gravity (USG), fasting

glucose, fasting insulin, HOMA-IR, and plasma copeptin. One-sample t-tests revealed pre-to-

post change values within groups. Pearson correlation coefficients (r) measured the strength of

association between variables at both baseline and 12 weeks, as well as correlations between

changes in variables over the course of the intervention.

All study subjects (n=29) were classified into three water consumption categories (i)

<500 g/day, (ii) 500-1,000 g/day, and (iii) >1,000 g/day to determine if any differences were

detected depending upon amount of drinking water consumed. One-way Analysis of Variance

examined differences in water consumption categories at 12 weeks and corresponding changes in

weight loss, BMI, body fat, fasting glucose, fasting insulin, HOMA-IR, and plasma copeptin.

One-sample t-tests revealed pre-to-post changes for these variables within the water categories.

Finally, subjects were paired according to both gender and total kilograms of weight lost

to eliminate these variables as potential confounding factors. Six subjects from the water group

(4 females, 2 males) were matched to subjects in the non-water group who were of the same

11

gender and had lost a similar amount of weight (<0.6 kg difference between paired subjects).

Subjects selected for pair-matching lost between 1.8 and 8.4 kg of total body weight. Paired

samples t-tests were performed to determine paired differences for fasting glucose, insulin,

HOMA-IR, and copeptin.

IV. Results

A total of 48 individuals completed the original study. Of these, 29 had glucose, insulin,

and HOMA-IR data available, and only these participants were included in the present

investigation. This subset consisted of overweight adults (BMI=31+1 kg/m2, age=62+1 years)

with 13 individuals assigned to the water and hypocaloric diet group and 16 assigned to the

hypocaloric diet group.

There were no baseline differences between groups with respect to age, BMI, body

weight, drinking water consumed, USG, fasting glucose, fasting insulin, HOMA-IR, or plasma

copeptin. Water group participants significantly reduced BMI, body weight, USG, and fasting

insulin with a significant increase in water consumption at the end of the intervention period (all

P<0.05). Non-water group subjects significantly reduced BMI, body weight, and plasma

copeptin at the conclusion of the intervention (all P<0.05). No group differences were noted in

pre-to-post changes in BMI, body weight, USG, fasting glucose, fasting insulin, HOMA-IR

score, or plasma copeptin (Table 1).

Several notable correlations between variables were detected. At baseline, body weight

correlated with drinking water consumed (r=-0.512, P<0.01); plasma copeptin correlated with

USG (r=0.424) and total grams of beverages consumed (r=-0.403) (P<0.05); fasting insulin

correlated with body weight (r=0.628, P<0.01) and grams of drinking water consumed (r=-0.378,

P<0.05); and HOMA-IR score correlated with body weight (r=0.658, P<0.01), USG (r=0.394,

P<0.05), and drinking water consumed (r=-0.373, P<0.05). At week-12, plasma insulin

correlated with body weight (r=0.542, P<0.01), USG (r=0.512, P<0.01), and copeptin (r=0.389,

P<0.05); and HOMA-IR score correlated with USG (r=0.530, P<0.01). Interestingly, change in

BMI correlated with change in USG (r=0.443, P=0.021) at the conclusion of the intervention.

Categorization of subjects into three water-consuming categories did not reveal

significant differences between groups with regard to changes in weight, BMI, kilograms of total

body fat, fasting glucose, fasting insulin, HOMA-IR, or plasma copeptin. In a secondary

12

analysis, subjects in the lowest water consuming category (<500 g/day) were compared to the

highest category (>1,000 g/day) to analyze differences in the same variables. No significant

differences were detected despite seemingly large differences in the means for fasting insulin

(-0.3+5 vs. -9.2+3 pmol/L, P=0.142) (Table 2). Notably, participants in the highest drinking

water category (>1,000 g/day), significantly reduced body weight, BMI, body fat, fasting insulin,

and HOMA-IR score from baseline to 12-weeks (all P<0.05). Participants in the lowest drinking

water category (<500 g/day) also experienced significant reductions in body weight, BMI, and

total body fat at the conclusion of the intervention (all P<0.05).

Furthermore, no paired differences were detected for fasting glucose, plasma insulin,

HOMA-IR, or plasma copeptin at the conclusion of the intervention. The ranges and means for

these variables among the participants pair-matched for gender and kilograms of weight lost are

displayed in Table 3.

V. Discussion

Despite a wealth of literature supporting the positive impact of increased water

consumption and weight loss on diabetes risk in older adults, our analyses did not clearly

demonstrate these benefits. The small sample size (n=29) likely contributed to the lack of

significant differences between water and non-water participants with regard to weight loss,

glucose, insulin, HOMA-IR, and copeptin.

Although pre-to-post changes in diabetes risk factors were not significantly different

between groups, important within-group changes were detected. All subjects successfully

reduced BMI and body weight at the conclusion of the hypocaloric diet intervention, regardless

of intervention group. However, those assigned to the water group also experienced

improvements in hydration status (demonstrated by decreased USG) and reductions in plasma

insulin concentration. Furthermore, several notable correlations between variables were detected.

At baseline, the amount of drinking water consumed correlated negatively with body weight and

fasting insulin, supporting the findings of previous research regarding the benefits of water

consumption. At the conclusion of the intervention, plasma insulin had a positive correlation

with copeptin and USG, and insulin resistance (HOMA-IR) increased as USG increased.

Furthermore, change in BMI correlated positively with change in USG, suggesting a possible

association between body composition and hydration status. These results support previous

13

research findings of positive correlations of plasma copeptin with components of metabolic

syndrome (which included fasting insulin levels and HOMA-IR). Positive correlations among

USG and insulin resistance, as well as positive change correlations among USG and BMI, may

further demonstrate associations between hydration status and diabetes risk.

According to current available literature, plasma copeptin concentrations in healthy

adults range from 0.44-44.3 pmol/L with a median value of 3.8 pmol/L (32). Additionally, men

tend to have higher plasma copeptin levels than women (6, 33, 34). For the entire sample

included in our investigation, plasma copeptin values ranged from 0.28-4.57 pmol/L with a

median value of 0.69 pmol/L. No gender differences were detected among the entire sample for

plasma copeptin at baseline, week 12, or pre-to-post changes, which led to our pair-match based

upon both weight loss and gender. Limitations exist with regard to our copeptin analysis.

Copeptin is greatly influenced by recent water consumption and fasting and therefore may not

reflect chronic hydration status. Furthermore, copeptin may be influenced by dietary habits.

Higher sodium intake may prompt AVP secretion, subsequently elevating plasma copeptin levels

(9, 35). Because copeptin analysis was not a component of the original investigation, participants

were not given specific instructions for fluid or sodium consumption prior to the overnight fast

before blood was drawn, potentially impacting our results. The clinical significance of plasma

copeptin as a diagnostic tool is still under investigation, and further research into its relevance is

warranted.

While analysis of diabetes risk factors according to levels of drinking water consumption

did not reveal significant differences between groups, those subjects who drank the most water

(>1,000 g/day) experienced reductions in body weight, BMI, body fat, insulin, and HOMA-IR,

indicating that increasing water consumption does have positive benefits for this population.

While the small sample size likely limited the statistical power to detect differences in

diabetes risk factors between groups, this preliminary study may be used to determine sample

sizes needed for future investigations. Using findings of this investigation (group mean

differences, standard deviations), it is estimated that future investigations would require a sample

size of at least 104 participants (52/group) in order to detect significant group differences in

weight loss, insulin, and HOMA-IR scores given the small-medium average effect size of 0.28

for these factors.

14

The increasing prevalence of overweight, obesity, and type 2 diabetes in older adults is a

public health concern. Successful approaches to loss and maintenance of body weight are

essential for lowering risk factors for diabetes. Although results of this investigation did not

clearly support the hypothesis, future studies are warranted to determine if health messages and

clinical practice should be altered to include recommendations on increasing water consumption

in conjunction with weight loss for the older adult population.

15

Figure 1. Associations between aging, water consumption, and diabetes risk; and areas to target

for intervention.

16

Table 1. Results: Summary table of participant characteristics and variables associated with

weight loss, water consumption, and diabetes risk (n=29).*

Variables Water Group

(n=13)

Non-water Group

(n=16)

Baseline Week12 Change Baseline Week12 Change

Age, years 62+1 ----- ----- 62+1 ----- -----

BMI, kg/m2a

31.3+1 28.9+1 -2.4+0.4 29.9+1 28.4+1 -1.4+0.3

Weight, kga 89.7+4 82.8+4 -7.0+1 86.1+4 81.9+4 -4.2+1

Drinking Water

Consumed, gb

359+87 1307+154 949+171a 501+142 361+110 -140+145

Urinary Specific

Gravity, UG 1+.001 1+.002 -.003+.001

a 1+.001 1+.002 -.0002+.001

Fasting Glucose,

mg/dl 87.8+4 86.2+4 -1.5+3 88.7+4 87.2+4 -1.5+2

Fasting Insulin,

pmol/L 39.0+4 30.5+4 -8.5+4

a 35.2+5 34.6+6 -0.6+3

HOMA-IR Score 1.2+0.1 0.9+0.1 -0.3+0.1 1.1+0.1 1.1+0.2 -0.01+0.1

Plasma Copeptin,

ng/ml 3.7+0.5 3.9+1 0.2+0.8 4.5+1 3.5+0.9 -1+0.4

a

*Presented as mean + SEM, for continuous variables. aSignificant differences detected from baseline to week 12 within groups (P<0.05).

bSignificant differences detected from baseline to week 12 between groups (P<0.05).

17

Table 2. Results: Group differences according to two drinking water categories at week 12 of the

intervention (n=25).*

Variables Drinking Water Categories at Week 12

<500 g/day

(n=13)

>1,000 g/day

(n=12)

Weight Lost, kg -4.7+1 -7.3+1

Change BMI, kg/m2 -1.6+0.4 -2.6+0.5

Change Body Fat, kg -3.5+0.8 -4.6+0.9

Change Fasting Glucose, mg/dl -1.7+3 -2.9+2

Change Fasting Insulin, pmol/L -0.3+5 -9.2+3

Change HOMA-IR Score -0.01+0.2 -0.3+0.1

Change Plasma Copeptin, ng/ml -0.5+0.8 -0.2+0.5

*Presented as mean + SEM, for continuous variables. No significant differences were detected.

18

Table 3. Results: Ranges and means for variables related to diabetes risk among participants

pair-matched for gender and kilograms of weight lost (n=12)*.

Intervention Group Minimum Maximum Mean +SEM

FPG, mg/dl

Water 54.3 100.9 83.9+7

Non-water 68.6 95.9 85.7+4

Insulin, pmol/L

Water 15.7 48.6 29.2+6

Non-water 9.6 79.3 28.2+10

HOMA-IR

Water 0.42 1.3 0.84+0.1

Non-water 0.28 2.6 0.88+0.3

Copeptin, ng/ml

Water 1.4 9.7 3.8+1

Non-water 2.5 15.8 5.3+2

*No significant differences were detected.

19

CHAPTER 3: Conclusions and Implications for Future Research

The prevalence of diabetes for Americans over 65 years is a staggering 26.9%, and 50%

of this age group is considered prediabetic (having IFG, IGT, and/or hemoglobin A1c 5.7% to

6.4%) (36, 37). Diabetes and prediabetes are major risk factors for cardiovascular and kidney

diseases, thus intervention strategies aimed at reducing diabetes risk factors in this population are

critical. Weight loss and increasing water consumption are two effective methods for improving

glucose tolerance and insulin resistance (17-22). The purpose of this study was to determine the

effects of weight loss in combination with increased water consumption on diabetes risk factors

in older adults. The water group significantly reduced their body weight, BMI, and fasting

insulin over the course of the 12-week intervention, while those in the non-water group did not

experience reductions in insulin. These findings indicate that weight loss in combination with

increased water consumption can have a beneficial impact on elevated insulin production.

However, the differences between groups with regard to diabetes risk factors (fasting glucose,

insulin, and HOMA-IR) were not significant. Investigations with larger sample sizes may detect

these differences.

Additional research is needed to address the possible role of the AVP system in glucose

homeostasis, insulin resistance, and diabetes mellitus. Standardization of hydration status and

dietary sodium intake at the time of copeptin measurement may be a necessary component of

future research designs. Participants in this investigation were not standardized with regard to

hydration or sodium intake, and copeptin analysis was not an aim of the original study,

potentially resulting in limitations for our analyses.

Despite a lack of statistical support for our hypothesis, future research should be

conducted to further explore this association between drinking water and improved glycemia.

Increasing water consumption, or replacement of caloric beverages with water are simple and

cost-effective strategies for body weight loss and maintenance. The addition of drinking water

recommendations to common healthcare practice may result in improved health outcomes with

relation to hydration, as well as diabetes risk for older adults. In conclusion, this type of

intervention may represent a feasible and potentially effective approach for reducing the

prevalence and progression to diabetes for at risk older adults.

20

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